Generate contextual images for web projects using the Gemini API. Produces hero backgrounds, OG cards, placeholder photos, textures, and style-matched variants.
Works with
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versiongemini-image-genExecute the skills CLI command in your project's root directory to begin installation:
Fetches gemini-image-gen from jezweb/claude-skills and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate gemini-image-gen. Access via /gemini-image-gen in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
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Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
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Generate contextual images for web projects using the Gemini API. Produces hero backgrounds, OG cards, placeholder photos, textures, and style-matched variants.
API Key: Set GEMINI_API_KEY as an environment variable. Get a key from https://aistudio.google.com/apikey if you don't have one.
export GEMINI_API_KEY="your-key-here"
Gather from the user or project context:
Use concrete photography parameters, not abstract adjectives. Read references/prompting-guide.md for the full framework.
Quick rules:
Generate a Python script (no dependencies beyond stdlib) that calls the Gemini API. The script should:
GEMINI_API_KEY from environmenthttps://generativelanguage.googleapis.com/v1beta/models/{model}:generateContent"responseModalities": ["TEXT", "IMAGE"] in generationConfiginlineData.data (base64) from candidate partsname-1.png, name-2.png)For style matching with a reference image, include the reference as an inlineData part before the text prompt, and use temperature 0.7 (instead of 1.0).
See references/api-pattern.md for the full implementation pattern including error handling and response parsing.
Critical: Never pass prompts via curl + bash arguments — shell escaping breaks on apostrophes. Always use Python's json.dumps() or write the prompt to a file first.
Use the image-processing skill for resizing, format conversion, or optimisation.
Show the generated images for review. Read the image files to display them inline if possible, otherwise describe what was generated and let the user open them.
Starting prompts — enhance with project-specific context (colours, mood, subject):
| Preset | Base Prompt |
|---|---|
hero-background |
"Wide atmospheric background, soft-focus, [colour tones], [mood], landscape 1920x1080" |
og-image |
"Clean branded card background, [brand colours], subtle gradient, 1200x630" |
placeholder-photo |
"Professional stock-style photo of [subject], natural lighting, warm tones" |
texture-pattern |
"Subtle repeating texture, [material], seamless tile, muted [colour]" |
product-shot |
"Product photography, [item] on [surface], soft studio lighting, clean background" |
| Use case | Model | Cost |
|---|---|---|
| Drafts, quick placeholders | gemini-2.5-flash-image |
Free (~500/day) |
| Final client assets | gemini-3-pro-image-preview |
~$0.04/image |
| Style-matched variants | gemini-3-pro-image-preview + reference image |
~$0.04/image |
Verify current model IDs if errors occur — they change frequently.
| When | Read |
|---|---|
| Building effective prompts | references/prompting-guide.md |
| API implementation details | references/api-pattern.md |
Make data-driven prioritization decisions faster
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Prerequisites
Time Estimate
30-60 minutes to see productivity improvements
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid when
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
jezweb/claude-skills
mattpocock/skills
parcadei/continuous-claude-v3
cursor/plugins
ailabs-393/ai-labs-claude-skills
pproenca/dot-skills
We added gemini-image-gen from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
Useful defaults in gemini-image-gen — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
gemini-image-gen fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
gemini-image-gen has been reliable in day-to-day use. Documentation quality is above average for community skills.
I recommend gemini-image-gen for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
We added gemini-image-gen from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
Solid pick for teams standardizing on skills: gemini-image-gen is focused, and the summary matches what you get after install.
Useful defaults in gemini-image-gen — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
We added gemini-image-gen from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
Registry listing for gemini-image-gen matched our evaluation — installs cleanly and behaves as described in the markdown.
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